Animals can easily adapt their bodies and movements to new, unstructured environments and situations. Robots cannot. While engineers construct robots from rigid, motorized mechanisms to precisely control their movements, vertebrates […]
Machine learning is transforming numerous aspects of modern society, and its expanding use in high-stakes applications calls for responsible development. In this talk, I will present my research on the […]
Generative modeling offers a powerful paradigm for designing novel functional DNA, RNA and protein sequences. In this talk, I introduce probabilistic experimental design methods to efficiently manufacture samples from generative […]
Abstract: Data-driven systems hold immense potential to positively impact society, but their reliability remains a challenge. Their outputs are often too brittle to changes in their training data, leaving them […]
This will be a hybrid event with in-person attendance in Levine 307 and virtual attendance on Zoom. ABSTRACT The Spring 2025 GRASP SFI Student Lightning Talks will highlight the research of […]
Quantum Dots: From Curiosity to Technological Impact The combination of quantum effects, nanometer dimensions and a chemical synthesis make quantum dots a platform for exploring new size-dependent fundamental properties and […]
Particle assemblies form interconnected pockets of empty space that are hot spots for activity in many applications and natural phenomenon that deal with particulate matter. In my lab we explore […]
Over the past decade, large-scale pre-training followed by alignment has revolutionized natural language processing and computer vision. Yet, robotics remains constrained by the scarcity of real-world data. In this talk, […]
Zoom link: https://upenn.zoom.us/j/98220304722 Abstract: Modern ML models produce valuable predictions across various applications, influencing people’s lives, opportunities, and scientific advancements. However, these systems can fail in unexpected ways, generating unreliable […]
Artificial intelligence (AI) is transforming scientific discovery, particularly in materials science, by accelerating the prediction and design of materials with desired properties. Traditional physics-based modeling of atomic systems is computationally […]
